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Brain disorders include any disabilities that affect the brain and come with different types, including neurological (Alzheimer\u2019s disease, Parkinson\u2019s disease, multiple sclerosis, stroke, epilepsy and seizures, etc.), sleep disorders, mental health disorders (depression, anxiety, etc.), and more. These diseases interfere with activities of daily living, worsening the quality of life and are often associated with social stigma. However, many disorders are preventable if diagnosed early. Therefore, early diagnosis is crucial for allowing patients to maintain their quality of life.<\/p>\n
Nowadays, real-world data, i.e., patient data collected from a variety of sources, and Artificial Intelligence (AI)\/Machine Learning (ML) have created new ways for personalized diagnosis and prognosis of complex brain disorders. Specifically, health data come in various formats, including actigraphy data, wearable sensors, speech via conversations between the patient and doctor, electronic health records, imaging, i.e., Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), biosignals, i.e., Polysomnography (PSG), questionnaires, and many more. Through the use of AI and ML methods, especially Natural Language Processing (NLP), Speech Processing, and Image Processing, valuable insights can be obtained. While various methods have been developed, approaches regarding interpretability, fusion of the different modalities, uncertainty estimation, or privacy issues remain as major challenges.<\/p>\n
This Workshop aims to bring together researchers with expertise relevant to the use of AI\/ML methods in the healthcare domain for discussing the latest advances in this emerging field.<\/p>\n